Intraventricular Meningiomas: Clinical-Pathological and Genetic Features of a Monocentric Series
Bibliographic record
Abstract
Intraventricular meningiomas (IVMs) are rare (0.5–5%) and usually low-grade (90% grade I) brain neoplasms. Their recurrence rate is lower than that of extra-axial meningiomas, but their surgical resection can be burdened with life-threatening complications, which represent the major cause of the reported 4% mortality. The aim of this study is to characterize the molecular portrait of IVMs to identify potential therapeutic targets. For this, we explored mutations and copy number variations (CNV) of 409 cancer-related genes and tumor mutational burden (TMB) of six cases, using next-generation sequencing. Five IVMs were grade I and one was grade II; none recurred, in spite of partial surgical resection in one case. NF2 mutation was the only recurring alteration and was present in three of the six IVMs, in association with SMARCB1 mutation in one case. None of the cases was hypermutated (TMB > 10 mutations/Mb). NF2-mutant progressing or recurring IVMs could potentially be treated with targeted therapies applied to other NF2-mutant tumors, as an alternative to surgery or radiosurgery, while in view of their low TMB they are unlikely candidates to immune check-point inhibition.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".